Exploiting Contextual Information for Speech/Non-Speech Detection
| Type of publication: | Conference paper |
| Citation: | Parthasarathi_TSD2008_2008 |
| Booktitle: | Text, Speech and Dialogue |
| Series: | Series of Lecture Notes In Artificial Intelligence (LNAI) |
| Volume: | 5246 |
| Year: | 2008 |
| Month: | 9 |
| Publisher: | Springer-Verlag Berlin, Heidelberg |
| Location: | Brno, Czech Republic |
| ISBN: | 978-3-540-87390-7 |
| Crossref: | parthasarathi:rr08-22: |
| Abstract: | In this paper, we investigate the effect of temporal context for speech/non-speech detection (SND). It is shown that even a simple feature such as full-band energy, when employed with a large-enough context, shows promise for further investigation. Experimental evaluations on the test data set, with a state-of-the-art multi-layer perceptron based SND system and a simple energy threshold based SND method, using the F-measure, show an absolute performance gain of 4.4% and 5.4% respectively. The optimal contextual length was found to be 1000 ms. Further numerical optimizations yield an improvement (3.37% absolute,',','), resulting in an absolute gain of 7.77% and 8.77% over the MLP based and energy based methods respectively. ROC based performance evaluation also reveals promising performance for the proposed method, particularly in low SNR conditions. |
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Idiap |
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| Added by: | [UNK] |
| Total mark: | 0 |
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